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DBMS > Apache Phoenix vs. Dgraph vs. Milvus vs. Spark SQL vs. TigerGraph

System Properties Comparison Apache Phoenix vs. Dgraph vs. Milvus vs. Spark SQL vs. TigerGraph

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDgraph  Xexclude from comparisonMilvus  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseDistributed and scalable native Graph DBMSA DBMS designed for efficient storage of vector data and vector similarity searchesSpark SQL is a component on top of 'Spark Core' for structured data processingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelRelational DBMSGraph DBMSVector DBMSRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitephoenix.apache.orgdgraph.iomilvus.iospark.apache.org/­sqlwww.tigergraph.com
Technical documentationphoenix.apache.orgdgraph.io/­docsmilvus.io/­docs/­overview.mdspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.com
DeveloperApache Software FoundationDgraph Labs, Inc.Apache Software Foundation
Initial release20142016201920142017
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192.3.4, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageJavaGoC++, GoScalaC++
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Linux
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonononono
Secondary indexesyesyesnono
SQL infoSupport of SQLyesnonoSQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methodsJDBCGraphQL query language
gRPC (using protocol buffers) API
HTTP API
RESTful HTTP APIJDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresuser defined functionsnononoyes
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesShardingyesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Synchronous replication via Raftnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynonononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyno infoPlanned for future releasesRole based access control and fine grained access rightsnoRole-based access control
More information provided by the system vendor
Apache PhoenixDgraphMilvusSpark SQLTigerGraph
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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More resources
Apache PhoenixDgraphMilvusSpark SQLTigerGraph
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